Devdutta Sadananda Niyogi

The influence of land-use change and landscape dynamics on the climate system: relevance to climate-change policy beyond the radiative effect of greenhouse gases.

Our paper documents that land-use change impacts regional and global climate through the surface-energy budget, as well as through the carbon cycle. The surface-energy budget effects may be more important than the carbon-cycle effects. However, land-use impacts on climate cannot be adequately quantified with the usual metric of ‘global warming potential’. A new metric is needed to quantify the human disturbance of the Earths surface-energy budget. This ‘regional climate change potential’ could offer a new metric for developing a more inclusive climate protocol. This concept would also implicitly provide a mechanism to monitor potential local-scale environmental changes that could influence biodiversity.

Simulation of Atmospheric Boundary Layer Processes Using Local- and Nonlocal-Closure Schemes

A soil‐vegetation‐atmospheric boundary layer model was developed to study the performance of two localclosure and two nonlocal-closure boundary layer mixing schemes for use in meteorological and air quality simulation models. Full interaction between the surface and atmosphere is achieved by representing surface characteristics and associated processes using a prognostic soil‐vegetation scheme and atmospheric boundary layer schemes. There are 30 layers in the lowest 3 km of the model with a high resolution near the surface. The four boundary layer schemes are tested by simulating atmospheric boundary layer structures over densely and sparsely vegetated regions using the observational data from the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) and from Wangara. Simulation results indicate that the near-surface turbulent fluxes predicted by the four boundary layer schemes differ from each other, even though the formulation used to represent the surface-layer processes is the same. These differences arise from the differing ways of representing subgrid-scale vertical mixing processes. Results also indicate that the vertical profiles of predicted parameters (i.e., temperature, mixing ratio, and horizontal winds) from the four mixed-layer schemes differ from each other, particularly during the daytime growth of the mixed layer. During the evening hours, after the mixed layer has reached its maximum depth, the differences among these respective predicted variables are found to be insignificant. There were some general features that were associated with each of the schemes in all of the simulations. Compared with observations, in all of the cases the simulated maximum depths of the boundary layer for each scheme were consistently either lower or higher, superadiabatic lapse rates were consistently either stronger or weaker, and the intensity of the vertical mixing was either stronger or weaker. Also, throughout the simulation period in all case studies, most of the differences in the predicted parameters are present in the surface layer and near the top of the mixed layer.

Comparison of Four Different Stomatal Resistance Schemes Using FIFE Observations

Stomatal resistance (Rs) calculation has a major impact on the surface energy partitioning that influences diverse boundary layer processes. Present operational limited area or mesoscale models have the Jarvis-type parameterization, whereas the microscale and the climate simulation models prefer physiological schemes for estimating Rs. The pivotal question regarding operational mesoscale models is whether an iterative physiological scheme needs to be adopted ahead of the analytical Jarvis-type formulation. This question is addressed by comparing the ability of three physiological schemes along with a typical Jarvistype scheme for predicting Rs using observations made during FIFE. The data used is typical of a C4-type vegetation, predominant in regions of high convective activity such as the semiarid Tropics and the southern United States grasslands. Data from three different intensive field campaigns are analyzed to account for vegetation and hydrological diversity. It is found that the Jarvis-type approach has low variance in the outcome due to a poor feedback for the ambient changes. The physiological models, on the other hand, are found to be quite responsive to the external environment. All three physiological schemes have a similar performance qualitatively, which suggests that the vapor pressure deficit approach or the relative humidity descriptor used in the physiological schemes may not yield different results for routine meteorological applications. For the data considered, the physiological schemes had a consistently better performance compared to the Jarvis-type scheme in predicting Rs outcome. All four schemes can, however, provide a reasonable estimate of the ensemble mean of the samples considered. A significant influence of the seasonal change in the minimum Rs in the Jarvis-type scheme was also noticed, which suggests the use of nitrogen-based information for improving the performance of the Jarvis-type scheme. A possible interactive influence of soil moisture on the capabilities of the four schemes is also discussed. Overall, the physiological schemes performed better under higher moisture availability.

UNCERTAINTY IN THE SPECIFICATION OF SURFACE CHARACTERISTICS: A STUDY OF PREDICTION ERRORS IN THE BOUNDARY LAYER

The effects of uncertainty in the specification of surface characteristics on simulated atmospheric boundary layer (ABL) processes and structure were investigated using a one-dimensional soil-vegetation-boundary layer model. Observational data from the First International Satellite Land Surface Climatology Project Field Experiment were selected to quantify prediction errors in simulated boundary-layer parameters. Several numerical 12-hour simulations were performed to simulate the convective boundary-layer structure, starting at 0700 LT 6 June 1987.In the control simulation, measured surface parameters and atmospheric data were used to simulate observed boundary-layer processes. In the remaining simulations, five surface parameters – soil texture, initial soil moisture, minimum stomatal resistance, leaf area index, and vegetation cover – were varied systematically to study how uncertainty in the specification of these surface parameters affects simulated boundary-layer processes.The simulated uncertainty in the specification of these five surface parameters resulted in a wide range of errors in the prediction of turbulent fluxes, mean thermodynamic structure, and the depth of the ABL. Under certain conditions uncertainty in the specifications of soil texture and minimum stomatal resistance had the greatest influence on the boundary-layer structure. A lesser but still moderately strong effect on the simulated ABL resulted from (1) a small decrease (4%) in the observed initial soil moisture (although a large increase [40%] had only a marginal effect), and (2) a large reduction (66%) in the observed vegetation cover. High uncertainty in the specification of leaf area index had only a marginal impact on the simulated ABL. It was also found that the variations in these five surface parameters had a negligible effect on the simulated horizontal wind fields. On the other hand, these variations had a significant effect on the vertical distribution of turbulent heat fluxes, and on the predicted maximum boundary-layer depth, which varied from about 1400–2300 m across the 11 simulations. Thus, uncertainties in the specification of surface parameters can significantly affect the simulated boundary-layer structure in terms of meteorological and air quality model predictions.

Hydrological Land Surface Response in a Tropical Regime and a Midlatitudinal Regime

A statistical‐dynamical study was performed on the role of hydrometeorological interactions in the midlatitudes and the semiarid Tropics. For this, observations from two field experiments, the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) and the Hydrological Atmospheric Pilot Experiment (HAPEX)‐Sahel, representative of the midlatitudes and the semiarid tropical conditions, and simulated results from a land surface model, Simplified Simple Biosphere (SSiB) model were statistically analyzed for direct and interaction effects. The study objectives were to test the hypothesis that there are significant differences in the land surface processes in the semiarid tropical and midlatitudinal regimes and to identify the nature of the differences in the evapotranspiration exchanges for the two biogeographical domains. Results suggest there are similarities in the direct responses but the interactions or the indirect feedback pathways could be very different. The arid tropical regimes are dominated through vegetative pathways (via variables such leaf area index, stomatal resistance, and vegetal cover); the midlatitudes show soil wetness (moisture)‐related feedback. In addition, for the midlatitudinal case, the vegetation and the soil surface acted in unison, leading to more interactive exchanges between the vegetation and the soil surface. The water-stressed semiarid tropical surface, on the other hand, showed response either directly between the vegetation and the atmosphere or between the soil and the atmosphere with very little interaction between the vegetation and the soil variables. Thus, the semiarid Tropics would require explicit bare ground and vegetation fluxes consideration, whereas the effective (combined vegetation and soil fluxes) surface representation used in various models may be more valid for the midlatitudinal case. This result also implied that with higher resource (water) availability the surface invested more in the surrounding environment. On the other hand, with poor resource availability (such as water stress in the tropical site), the surface components retain individual resources without sharing.

Assimilating Surface Data to Improve the Accuracy of Atmospheric Boundary Layer Simulations

Large errors in atmospheric boundary layer (ABL) simulations can be caused by inaccuracies in the specification of surface characteristics in addition to assumptions and simplifications made in boundary layer formulations or other model deficiencies. For certain applications, such as air quality studies, these errors can have significant effects. To reduce such errors, a continuous surface data assimilation technique is developed. In this technique, surface-layer temperature and water vapor mixing ratio are directly assimilated by using the analyzed surface data. Then, the difference between the observations and model results is used to calculate adjustments to the surface fluxes of sensible and latent heat. These adjustments are then used to calculate a new estimate of the ground temperature, thereby affecting the simulated surface fluxes on the subsequent time step. This indirect data assimilation is applied simultaneously with the direct assimilation of surface data in the model’s lowest layer, thereby maintaining greater consistency between the ground temperature and the surface-layer mass-field variables. A one-dimensional model was used to study the improvements that result from applying this technique for ABL simulations in two cases. It was found that application of the new technique led to significant reductions in ABL modeling errors.

Marine Boundary-Layer Variability Over The Indian Ocean During Indoex (1998)

The variability in boundary-layerstructure over the Indian Ocean during a north-eastmonsoon and the factors influencing it areinvestigated. This study was made possible as acomponent of the Indian Ocean Experiment (INDOEX),conducted from February 19 to March 30, 1998. The dataused are, surface-layer mean and turbulencemeasurements of temperature, humidity and wind, andvertical soundings of temperature and humidity.Significant spatio-temporal variability was observedin the boundary-layer structure throughout the cruise.The ITCZ was characterized as the region withstrongest winds and maximum surface turbulent fluxesof momentum and heat. One of the important findingsfrom this study was a strong influence of continentalair masses on the boundary-layer structure in theNorthern Hemisphere, even at a distance of 600 km offthe Indian coast. This was generally evident in theform of an elevated plume of dry continental airbetween altitudes of 1500 m and 2700 m. Advection ofcontinental aerosols in this layer presents potentialfor significant entrainment into shallow clouds inthis region, which eventually feed deeper clouds atthe ITCZ. This finding provides an explanation foranomalous higher aerosol concentrations found duringprevious studies. The structure of the marineboundary layer was influenced by various factors suchas proximity to land, an anomalous warm pool in theocean and the ITCZ. In the southern hemisphere, theboundary-layer height was primarily governed bysurface-layer sensible heat flux and was found to behighest in the vicinity of the ITCZ. North of theequator it was strongly influenced by land-air-seainteractions. In addition to this synoptic modulation,there was also a significant diurnal variability inthe boundary-layer height.

Comparison of Four Different Stomatal Resistance Schemes Using FIFE Data. Part II: Analysis of Terrestrial Biospheric–Atmospheric Interactions

Stomatal resistance (Rs) forms a pivotal component of the surface energy budget and of the terrestrial biosphere‐atmosphere interactions. Using a statistical‐graphical technique, the Rs-related interactions between different atmospheric and physiological variables are resolved explicitly from observations made during the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE). A similar analysis was undertaken for the Rs parameterization schemes, as used in the present models. Three physiological schemes (the Ball‐Woodrow‐Berry, Kim and Verma, and Jacobs) and one operational Jarvis-type scheme were evaluated in terms of their ability to replicate the terrestrial biosphere‐atmosphere interactions. It was found that all of the Rs parameterization schemes have similar qualitative behavior for routine meteorological applications (without carbon assimilation). Compared to the observations, there was no significant difference found in employing either the relative humidity or the vapor pressure deficit as the humidity descriptor in the analysis. Overall, the relative humidity‐based interactions were more linear than the vapor pressure deficit and hence could be considered more convenient in the scaling exercises. It was found that with high photosynthesis rates, all of the schemes had similar behavior. It was found with low assimilation rates, however, that the discrepancies and nonlinearity in the interactions, as well as the uncertainties, were exaggerated.

Teleconnections between tropical pacific sea surface temperature anomalies and North Carolina precipitation anomalies during El Niño events

Linear teleconnections of El Nino events and precipitation over a regional coastal land mass were analyzed. Two statistical techniques were used. First, the Empirical Orthogonal Function extracted major variances of the monthly tropical Pacific sea surface temperature anomalies and coastal North Carolina precipitation anomalies. Second, the Canonical Correlation Analysis calculated the linear combinations of the anomaly data sets that were highly correlated. The results show that El Nino-related precipitation anomalies along the North Carolina coast were positive from November to May and negative between June and October consistent with large-scale studies. Results indicate simple, linear statistical techniques can be effectively adopted to determine teleconnections on a local scale.

A dynamic statistical experiment for atmospheric interactions

Interactions among atmospheric parameters exist at different scales. The pristine approach for observational or model data analysis involves changing the input parameters one at a time (OAT) and studying the effect on the system. Limitations of this approach for atmospheric applications are discussed. A fractional factorial (FF) based study is evolved and a methodology is outlined involving dynamic graphical analysis. Observational data from the FIFE and HAPEX‐MOBILHY experiments are utilized with a vegetation and soil moisture scheme dynamically coupled in a planetary boundary layer model to demonstrate the robustness of this approach. Both low‐resolution and high‐resolution designs are considered. Various aspects of the vegetation‐atmosphere interactions are delineated. Results obtained from the interaction‐based FF approach differ considerably from the earlier OAT‐type studies.